Python for finance: apply powerful finance models and quantitative analysis with python (Record no. 21728)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 06336 a2200205 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20230802060838.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 230726b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 978-1787125698 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 005.133 |
| Item number | YAN |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Yan, Yuxing |
| 245 ## - TITLE STATEMENT | |
| Title | Python for finance: apply powerful finance models and quantitative analysis with python |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 2nd. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Mumbai: |
| Name of publisher, distributor, etc. | Packt Publishing Limited, |
| Date of publication, distribution, etc. | 2017. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xvii., 558 p. |
| Other physical details | ref., ind. |
| Dimensions | 24 cm x 18 cm |
| 500 ## - GENERAL NOTE | |
| General note | Recommended By: Banikanta Mishra<br/>------------------------------------------------------ |
| 521 ## - TARGET AUDIENCE NOTE | |
| Target audience note | Content<br/><br/>Chapter 1: Python Basics<br/>Python installation<br/>Variable assignment, empty space, and writing our own programs<br/>Writing a Python function<br/>Python loops<br/>Data input<br/>Data manipulation<br/>Data output<br/>Exercises<br/>Summary<br/><br/>Chapter 2: Introduction to Python Modules<br/>What is a Python module?<br/>Introduction to NumPy<br/>Introduction to SciPy<br/>Introduction to matplotlib<br/>Introduction to statsmodels<br/>Introduction to pandas<br/>Python modules related to finance<br/>Introduction to the pandas_reader module<br/>Two financial calculators<br/>How to install a Python module<br/>Module dependency<br/>Exercises<br/>Summary<br/><br/>Chapter 3: Time Value of Money<br/>Introduction to time value of money<br/>Writing a financial calculator in Python<br/>Definition of NPV and NPV rule<br/>Definition of IRR and IRR rule<br/>Definition of payback period and payback period rule<br/>Writing your own financial calculator in Python<br/>Two general formulae for many functions<br/>Exercises<br/>Summary<br/>Chapter 4: Sources of Data<br/>Diving into deeper concepts<br/>Summary<br/><br/>Chapter 5: Bond and Stock Valuation<br/>Introduction to interest rates<br/>Term structure of interest rates<br/>Bond evaluation<br/>Stock valuation<br/>A new data type – dictionary<br/>Summary<br/><br/>Chapter 6: Capital Asset Pricing Model<br/>Introduction to CAPM<br/>Moving beta<br/>Adjusted beta<br/>Extracting output data<br/>Simple string manipulation<br/>Python via Canopy<br/>References<br/>Exercises<br/>Summary<br/><br/>Chapter 7: Multifactor Models and Performance Measures<br/>Introduction to the Fama-French three-factor model<br/>Fama-French three-factor model<br/>Fama-French-Carhart four-factor model and Fama-French five-factor model<br/>Implementation of Dimson (1979) adjustment for beta<br/>Performance measures<br/>How to merge different datasets<br/>References<br/>Exercises<br/>Summary<br/><br/>Chapter 8: Time-Series Analysis<br/>Introduction to time-series analysis<br/>Merging datasets based on a date variable<br/>Understanding the interpolation technique<br/>Tests of normality<br/>52-week high and low trading strategy<br/>Estimating Roll's spread<br/>Estimating Amihud's illiquidity<br/>Estimating Pastor and Stambaugh (2003) liquidity measure<br/>Fama-MacBeth regression<br/>Durbin-Watson<br/>Python for high-frequency data<br/>Spread estimated based on high-frequency data<br/>Introduction to CRSP<br/>References<br/>Exercises<br/>Summary<br/><br/>Chapter 9: Portfolio Theory<br/>Introduction to portfolio theory<br/>A 2-stock portfolio<br/>Optimization – minimization<br/>Forming an n-stock portfolio<br/>Constructing an optimal portfolio<br/>Constructing an efficient frontier with n stocks<br/>References<br/>Exercises<br/>Summary<br/><br/>Chapter 10: Options and Futures<br/>Introducing futures<br/>Payoff and profit/loss functions for call and put options<br/>European versus American options<br/>Black-Scholes-Merton option model on non-dividend paying stocks<br/>Generating our own module p4f<br/>European options with known dividends<br/>Various trading strategies<br/>Put-call parity and its graphic presentation<br/>Binomial tree and its graphic presentation<br/>Hedging strategies<br/>Implied volatility<br/>Binary-search<br/>Retrieving option data from Yahoo! Finance<br/>Volatility smile and skewness<br/>References<br/>Exercises<br/>Summary<br/><br/>Chapter 11: Value at Risk<br/>Introduction to VaR<br/>Normality tests<br/>Skewness and kurtosis<br/>Modified VaR<br/>VaR based on sorted historical returns<br/>Simulation and VaR<br/>VaR for portfolios<br/>Backtesting and stress testing<br/>Expected shortfall<br/>References<br/>Exercises<br/>Summary<br/><br/>Chapter 12: Monte Carlo Simulation<br/>Importance of Monte Carlo Simulation<br/>Generating random numbers from a standard normal distribution<br/>Generating random numbers with a seed<br/>Generating random numbers from a uniform distribution<br/>Using simulation to estimate the pi value<br/>Generating random numbers from a Poisson distribution<br/>Selecting m stocks randomly from n given stocks<br/>With/without replacements<br/>Distribution of annual returns<br/>Simulation of stock price movements<br/>Graphical presentation of stock prices at options' maturity dates<br/>Replicating a Black-Scholes-Merton call using simulation<br/>Liking two methods for VaR using simulation<br/>Capital budgeting with Monte Carlo Simulation<br/>Python SimPy module<br/>Comparison between two social policies – basic income and basic job<br/>Finding an efficient frontier based on two stocks by using simulation<br/>Constructing an efficient frontier with n stocks<br/>Long-term return forecasting<br/>Efficiency, Quasi-Monte Carlo, and Sobol sequences<br/>References<br/>Exercises<br/>Summary<br/><br/>Chapter 13: Credit Risk Analysis<br/>Introduction to credit risk analysis<br/>Credit rating<br/>Credit spread<br/>YIELD of AAA-rated bond, Altman Z-score<br/>Using the KMV model to estimate the market value of total assets and its volatility<br/>Term structure of interest rate<br/>Distance to default<br/>Credit default swap<br/>References<br/>Exercises<br/>Summary<br/><br/>Chapter 14: Exotic Options<br/>European, American, and Bermuda options<br/>Chooser options<br/>Shout options<br/>Binary options<br/>Rainbow options<br/>Pricing average options<br/>Pricing barrier options<br/>Barrier in-and-out parity<br/>Graph of up-and-out and up-and-in parity<br/>Pricing lookback options with floating strikes<br/>References<br/>Exercises<br/>Summary<br/><br/>Chapter 15: Volatility, Implied Volatility, ARCH, and GARCH<br/>Conventional volatility measure – standard deviation<br/>Tests of normality<br/>Estimating fat tails<br/>Lower partial standard deviation and Sortino ratio<br/>Test of equivalency of volatility over two periods<br/>Test of heteroskedasticity, Breusch, and Pagan<br/>Volatility smile and skewness<br/>Graphical presentation of volatility clustering<br/>The ARCH model<br/>Simulating an ARCH (1) process<br/>The GARCH model<br/>Simulating a GARCH process<br/>Simulating a GARCH (p,q) process using modified garchSim()<br/>GJR_GARCH by Glosten, Jagannanthan, and Runkle<br/>References<br/>Exercises<br/>Summary |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| General subdivision | Big Data and Business Intelligence |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Books |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Date acquired | Source of acquisition | Cost, normal purchase price | Inventory number | Total Checkouts | Full call number | Barcode | Date last seen | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | KEIC | KEIC | 07/21/2023 | Kushal Books | 1899.00 | IN275 | 005.133, YAN | 22462 | 10/13/2024 | 7467.00 | 07/21/2023 | Books |